Measuring productivity in multi-product firms

Share this project

New IGC study will collect data on productivity in ready-made garment factories across the world

Information will be compared against international standards to accurately compare factories in ten countries (including five IGC partner countries)

Will be the most comprehensive data ever collected

Sustained increases in income are not possible without increases in productivity. This cross-country study compares the efficiency of production lines in hundreds of firms which make ready-made garments (RMG). 10 countries are being studied including five IGC countries: Bangladesh, Myanmar, Pakistan, India-Central and Ethiopia. The research will help gain insights into which factors affect productivity in developing countries.

The researchers will study productivity by looking at sewing sections in garment factories and measuring efficiency by analysing the number of minutes the factory is taking to sew a specific piece of garment. This data will be compared against international standards which will allow the researchers to accurately compare firms across countries. In particular, the researchers will compare the productivity of lower-income countries such as Bangladesh and Myanmar against the performance of countries such as Sri Lanka, China and Indonesia which are perceived to have higher productivity.

The data collection exercise is going to be large and complicated: the data involved comes from a variety of different reports and each factory keeps data in different ways. For an idea of scale, a typical factory with 20 production lines results in about 300,000 pieces of data each year. Once compiled, however, this data will be the most comprehensive data ever collected on the manufacturing sectors in low-income countries.

The main stakeholders in this project are owners and workers in the RMG sector. Once the data is collected, the IGC will hold dissemination events with factory owners and workers representatives to track the impact of our findings. This data will then be made freely available to researchers and stakeholders through a dedicated website.